estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. this study aimed to use the particle swarm optimization (pso) algorithm for automatic calibration of the hec-hms hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff pr...

Abstract This paper introduces a multi-objective variant of the marine predators algorithm (MPA) called improved (MOIMPA), which incorporates concepts from Quantum theory. By leveraging theory, MOIMPA aims to enhance MPA’s ability balance between exploration and exploitation find optimal solutions. The utilizes concept inspired by Schrödinger wave function determine position particles in search...

Topology optimization (TO), which is a design technique that does not require parameters, has been attracting attention. TO high degree of freedom and can obtain novel shape suitable for desired purposes. However, the characteristics obtained may be greatly damaged due to uncertainty such as variations in material properties. Also, when multi-objective considered, an increase calculation load b...

A multi-condition multi-objective optimization method that can find Pareto front over a defined condition space is developed for the first time using deep reinforcement learning. Unlike conventional methods which perform at single condition, present learns correlations between conditions and optimal solutions. The exclusive capability of examined in solutions novel modified Kursawe benchmark pr...

the purpose of this paper is multi-objective optimization of refrigeration cycle by optimization of all components of the cycle contains heat exchangers, air condenser, evaporator and super-heater. studied refrigeration cycle is compression refrigeration cycle of unit 132 third refineries in south pars that provide chilled water for cooling refinery equipment's. cycle will be performed by ...

Portfolio optimization is a multi-objective problem (MOOP) with risk and profit, or some form of the two, as competing objectives. Single-objective portfolio requires trade-off coefficient to be specified in order balance two Erwin Engelbrecht proposed set-based approach single-objective optimization, namely, particle swarm (SBPSO). SBPSO selects sub-set assets that search space for secondary t...